In Boston University's lab, a robot arm conducts experiments to find the most energy-efficient shape, crushing 3D printed structures and recording data to create better shapes iteratively.
The robot, MAMA BEAR, utilizes Bayesian optimization methodology, tweaking design and dimensions based on past experiments to improve structures' impact absorption capabilities.
Keith Brown's team at KABlab has been evolving MAMA BEAR since 2018, setting it on a journey to create shapes with high mechanical energy absorption efficiency.
The continuous three-year experiment aims to refine the shapes for maximum energy absorption, showcasing the potential of robotic autonomy in engineering research.
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